In the domain of image processing, the improvement of the quality of images is a well-known problem to be solved. Such improvement is required for many technical applications, such as biological applications. In the domain of biological analysis, in vitro analysis is carried out on a biological sample to identify the type of micro-organisms potentially present in the biological sample. Such analysis can be performed by associating the biological sample with a specific environment such as a specific growth medium. The specific environment can be located, for example, in a Petri dish. The specific environment is adapted to the biological sample to be analyzed to allow the growth of micro-organisms. The Petri dish comprising the biological sample and the specific environment is then put in an incubator to generate the growth of micro-organisms.
After the incubation process, an analysis of the surface of the specific environment is performed to determine the type of micro-organisms that have grown in the Petri dish. The analysis comprises several steps, including illumination of the surface of the Petri dish with an imaging system as described in the published European application EP2520923. The imaging system comprises several illumination sources located around the biological sample. Each illumination source illuminates the biological sample from a different direction. A fixed position camera takes various images of a same surface of the Petri dish. A photometric stereo process is then applied to combine the data captured from the various images to provide a deepness map or a raised relief map of the surface of the Petri dish comprising objects such as micro-organisms.
Due to the different illumination directions of the various illumination sources and the specific nature of the micro-organisms, bright zones, such as specular zones, may appear. Bright zones correspond to high intensity pixels associated with a highlighted or specular zone in an image. During image processing procedures such as segmentation, object recognition or surface reconstruction, such bright and dark zones may cause a distortion effect on the corresponding output maps. This distortion effect may lead to an incorrect representation of the surface object on the deepness map.
In a similar manner, when considering an object having a determined height, other than the content of a Petri dish, dark zones may appear. During image processing procedures, such dark zones may also cause a distortion effect on the corresponding deepness map and thus lead to an incorrect representation of the object on the deepness map.
In the prior art, several methods for removing specular zones are disclosed. One of the methods comprises steps for identifying the specular zones within several images of a same object and then providing a single corrected image of the object where the pixels related to the specular zones are replaced with corrected pixel values.
However, in the present example, the multiple images of the object taken under different illumination directions must not be reduced after removing bright or dark zones. Indeed, each image of the object provides relevant information regarding the distribution of light on the object for further determination of the surface of the object during the photometric stereo process in order to identify the nature of the micro-organisms.
As a result, there is a need to improve the quality of the images of an object, each image being taken under different illumination conditions with a fixed position camera to prevent the occurrence of image distortion caused by bright and dark zones in such images, the aim being to retain the multiplicity of the images after improving the quality of the images and also to retain the distribution of intensity of illumination sources for each image.